Knowledge Acquisition

Knowledge acquisition, the process by which systems learn and integrate new information, is a central focus in artificial intelligence research, particularly concerning large language models (LLMs). Current research investigates how LLMs acquire and retain factual knowledge, exploring factors like knowledge entropy, training data characteristics, and the effectiveness of various learning strategies including knowledge distillation, reinforcement learning, and self-teaching. These efforts aim to improve LLMs' ability to learn continuously, handle uncertainty, and ultimately enhance their performance in knowledge-intensive tasks, impacting fields like robotics, education, and question answering.